scholarly journals Both Simulation and Sequencing Data Reveal Multiple SARS-CoV-2 Variants Coinfection in COVID-19 Pandemic

2021 ◽  
Author(s):  
Yinhu Li ◽  
Yiqi Jiang ◽  
Zhengtu Li ◽  
Yonghan Yu ◽  
Jiaxing Chen ◽  
...  
Keyword(s):  
Linear Relationship ◽  
Maximal Clique ◽  
Respiratory Pathogens ◽  
Sequencing Data ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide Variants ◽  
Heterozygous Snps ◽  
Single Nucleotide ◽  
Vaccine Protection ◽  
Viral Shedding

AbstractSARS-CoV-2 is a single-stranded RNA betacoronavirus with a high mutation rate. The rapidly emerged SARS-CoV-2 variants could increase the transmissibility, aggravate the severity, and even fade the vaccine protection. Although the coinfections of SARS-CoV-2 with other respiratory pathogens have been reported, whether multiple SARS-CoV-2 variants coinfection exists remains controversial. This study collected 12,986 and 4,113 SARS-CoV-2 genomes from the GISAID database on May 11, 2020 (GISAID20May11) and April 1, 2021 (GISAID21Apr1), respectively. With the single-nucleotide variants (SNV) and network clique analysis, we constructed the single-nucleotide polymorphism (SNP) coexistence networks and noted the SNP number of the maximal clique as the coinfection index. The coinfection indices of GISAID20May11 and GISAID21Apr1 datasets were 16 and 34, respectively. Simulating the transmission routes and the mutation accumulations, we discovered the linear relationship between the coinfection index and the coinfected variant number. Based on the linear relationship, we deduced that the COVID-19 cases in the GISAID20May11 and GISAID21Apr1 datasets were coinfected with 2.20 and 3.42 SARS-CoV-2 variants on average. Additionally, we performed Nanopore sequencing on 42 COVID-19 patients to explore the virus mutational characteristics. We found the heterozygous SNPs in 41 COVID-19 cases, which support the coinfection of SARS-CoV-2 variants and challenge the accuracy of phylogenetic analysis. In conclusion, our findings reported the coinfection of SARS-CoV-2 variants in COVID-19 patients, demonstrated the increased coinfected variants number in the epidemic, and provided clues for the prolonged viral shedding and severe symptoms in some cases.

scholarly journals Implications of Genetic Distance to Reference and De Novo Genome Assembly for Clinical Genomics in Africans

2020 ◽  
Author(s):  
Daniel Shriner ◽  
Adebowale Adeyemo ◽  
Charles Rotimi
Keyword(s):  
Genetic Distance ◽  
De Novo ◽  
Reference Sequence ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
De Novo Genome Assembly ◽  
Single Nucleotide ◽  
Clinical Genomics ◽  
Advantages And Disadvantages ◽  
False Discovery

In clinical genomics, variant calling from short-read sequencing data typically relies on a pan-genomic, universal human reference sequence. A major limitation of this approach is that the number of reads that incorrectly map or fail to map increase as the reads diverge from the reference sequence. In the context of genome sequencing of genetically diverse Africans, we investigate the advantages and disadvantages of using a de novo assembly of the read data as the reference sequence in single sample calling. Conditional on sufficient read depth, the alignment-based and assembly-based approaches yielded comparable sensitivity and false discovery rates for single nucleotide variants when benchmarked against a gold standard call set. The alignment-based approach yielded coverage of an additional 270.8 Mb over which sensitivity was lower and the false discovery rate was higher. Although both approaches detected and missed clinically relevant variants, the assembly-based approach identified more such variants than the alignment-based approach. Of particular relevance to individuals of African descent, the assembly-based approach identified four heterozygous genotypes containing the sickle allele whereas the alignment-based approach identified no occurrences of the sickle allele. Variant annotation using dbSNP and gnomAD identified systematic biases in these databases due to underrepresentation of Africans. Using the counts of homozygous alternate genotypes from the alignment-based approach as a measure of genetic distance to the reference sequence GRCh38.p12, we found that the numbers of misassemblies, total variant sites, potentially novel single nucleotide variants (SNVs), and certain variant classes (e.g., splice acceptor variants, stop loss variants, missense variants, synonymous variants, and variants absent from gnomAD) were significantly correlated with genetic distance. In contrast, genomic coverage and other variant classes (e.g., ClinVar pathogenic or likely pathogenic variants, start loss variants, stop gain variants, splice donor variants, incomplete terminal codons, variants with CADD score ≥20) were not correlated with genetic distance. With improvement in coverage, the assembly-based approach can offer a viable alternative to the alignment-based approach, with the advantage that it can obviate the need to generate diverse human reference sequences or collections of alternate scaffolds.

scholarly journals Bacsnp: Using Single Nucleotide Polymorphism (SNP) Specificities and Frequencies to Identify Genotype Composition in Baculoviruses

Viruses ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 625 ◽  
Author(s):  
Jörg T. Wennmann ◽  
Jiangbin Fan ◽  
Johannes A. Jehle
Keyword(s):  
Nucleotide Polymorphisms ◽  
Downstream Process ◽  
Sequencing Data ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Natural Isolates ◽  
Genotype Composition ◽  
R Programming ◽  
Dsdna Viruses ◽  
Virus Isolates

Natural isolates of baculoviruses (as well as other dsDNA viruses) generally consist of homogenous or heterogenous populations of genotypes. The number and positions of single nucleotide polymorphisms (SNPs) from sequencing data are often used as suitable markers to study their genotypic composition. Identifying and assigning the specificities and frequencies of SNPs from high-throughput genome sequencing data can be very challenging, especially when comparing between several sequenced isolates or samples. In this study, the new tool “bacsnp”, written in R programming langue, was developed as a downstream process, enabling the detection of SNP specificities across several virus isolates. The basis of this analysis is the use of a common, closely related reference to which the sequencing reads of an isolate are mapped. Thereby, the specificities of SNPs are linked and their frequencies can be used to analyze the genetic composition across the sequenced isolate. Here, the downstream process and analysis of detected SNP positions is demonstrated on the example of three baculovirus isolates showing the fast and reliable detection of a mixed sequenced sample.

scholarly journals Highly multiplexed, fast and accurate nanopore sequencing for verification of synthetic DNA constructs and sequence libraries

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Andrew Currin ◽  
Neil Swainston ◽  
Mark S Dunstan ◽  
Adrian J Jervis ◽  
Paul Mulherin ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Dna Sequencing ◽  
Cost Effective ◽  
Polymorphism Analysis ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Synthetic Dna ◽  
Design Build ◽  
Hardware Costs

Abstract Synthetic biology utilizes the Design–Build–Test–Learn pipeline for the engineering of biological systems. Typically, this requires the construction of specifically designed, large and complex DNA assemblies. The availability of cheap DNA synthesis and automation enables high-throughput assembly approaches, which generates a heavy demand for DNA sequencing to verify correctly assembled constructs. Next-generation sequencing is ideally positioned to perform this task, however with expensive hardware costs and bespoke data analysis requirements few laboratories utilize this technology in-house. Here a workflow for highly multiplexed sequencing is presented, capable of fast and accurate sequence verification of DNA assemblies using nanopore technology. A novel sample barcoding system using polymerase chain reaction is introduced, and sequencing data are analyzed through a bespoke analysis algorithm. Crucially, this algorithm overcomes the problem of high-error rate nanopore data (which typically prevents identification of single nucleotide variants) through statistical analysis of strand bias, permitting accurate sequence analysis with single-base resolution. As an example, 576 constructs (6 × 96 well plates) were processed in a single workflow in 72 h (from Escherichia coli colonies to analyzed data). Given our procedure’s low hardware costs and highly multiplexed capability, this provides cost-effective access to powerful DNA sequencing for any laboratory, with applications beyond synthetic biology including directed evolution, single nucleotide polymorphism analysis and gene synthesis.

scholarly journals neoepiscope improves neoepitope prediction with multivariant phasing

2019 ◽  
Vol 36 (3) ◽  
pp. 713-720 ◽  
Author(s):  
Mary A Wood ◽  
Austin Nguyen ◽  
Adam J Struck ◽  
Kyle Ellrott ◽  
Abhinav Nellore ◽  
...  
Keyword(s):  
False Negative ◽  
Supplementary Information ◽  
Supplementary File ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Somatic Variant ◽  
Negative Results ◽  
Multiple Datasets ◽  
False Negative Results

Abstract Motivation The vast majority of tools for neoepitope prediction from DNA sequencing of complementary tumor and normal patient samples do not consider germline context or the potential for the co-occurrence of two or more somatic variants on the same mRNA transcript. Without consideration of these phenomena, existing approaches are likely to produce both false-positive and false-negative results, resulting in an inaccurate and incomplete picture of the cancer neoepitope landscape. We developed neoepiscope chiefly to address this issue for single nucleotide variants (SNVs) and insertions/deletions (indels). Results Herein, we illustrate how germline and somatic variant phasing affects neoepitope prediction across multiple datasets. We estimate that up to ∼5% of neoepitopes arising from SNVs and indels may require variant phasing for their accurate assessment. neoepiscope is performant, flexible and supports several major histocompatibility complex binding affinity prediction tools. Availability and implementation neoepiscope is available on GitHub at https://github.com/pdxgx/neoepiscope under the MIT license. Scripts for reproducing results described in the text are available at https://github.com/pdxgx/neoepiscope-paper under the MIT license. Additional data from this study, including summaries of variant phasing incidence and benchmarking wallclock times, are available in Supplementary Files 1, 2 and 3. Supplementary File 1 contains Supplementary Table 1, Supplementary Figures 1 and 2, and descriptions of Supplementary Tables 2–8. Supplementary File 2 contains Supplementary Tables 2–6 and 8. Supplementary File 3 contains Supplementary Table 7. Raw sequencing data used for the analyses in this manuscript are available from the Sequence Read Archive under accessions PRJNA278450, PRJNA312948, PRJNA307199, PRJNA343789, PRJNA357321, PRJNA293912, PRJNA369259, PRJNA305077, PRJNA306070, PRJNA82745 and PRJNA324705; from the European Genome-phenome Archive under accessions EGAD00001004352 and EGAD00001002731; and by direct request to the authors. Supplementary information Supplementary data are available at Bioinformatics online.

Complete plastome sequences of Picea asperata and P. crassifolia and comparative analyses with P. abies and P. morrisonicola

Genome ◽  
2019 ◽  
Vol 62 (5) ◽  
pp. 317-328
Author(s):  
Fangqun Ouyang ◽  
Jiwen Hu ◽  
Junchen Wang ◽  
Juanjuan Ling ◽  
Zhi Wang ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Phylogenetic Trees ◽  
Sympatric Species ◽  
Sequencing Data ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Variable Regions ◽  
Focal Species ◽  
Phylogenetic Reconstructions ◽  
Picea Asperata

Picea asperata and P. crassifolia have sympatric ranges and are closely related, but the differences between these species at the plastome level are unknown. To better understand the patterns of variation among Picea plastomes, the complete plastomes of P. asperata and P. crassifolia were sequenced. Then, the plastomes were compared with the complete plastomes of P. abies and P. morrisonicola, which are closely and distantly related to the focal species, respectively. We also used these sequences to construct phylogenetic trees to determine the relationships among and between the four species as well as additional taxa from Pinaceae and other gymnosperms. Analysis of our sequencing data allowed us to identify 438 single nucleotide polymorphism (SNPs) point mutation events, 95 indel events, four inversion events, and seven highly variable regions, including six gene spacer regions (psbJ-petA, trnT-psaM, trnS-trnD, trnL-rps4, psaC-ccsA, and rps7-trnL) and one gene (ycf1). The highly variable regions are appropriate targets for future use in the phylogenetic reconstructions of closely related, sympatric species of Picea as well as Pinaceae in general.

RESEARCH ON PARAMETERIZED ALGORITHMS OF THE INDIVIDUAL HAPLOTYPING PROBLEM

2007 ◽  
Vol 05 (03) ◽  
pp. 795-816 ◽  
Author(s):  
MINZHU XIE ◽  
JIAN'ER CHEN ◽  
JIANXIN WANG
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Time Complexity ◽  
Maximum Length ◽  
Parameterized Algorithms ◽  
Sequencing Data ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide Polymorphism Site ◽  
Single Nucleotide ◽  
The Individual

The individual haplotyping problem is a computing problem of reconstructing two haplotypes for an individual based on several optimal criteria from one's fragments sequencing data. This paper is based on the fact that the length of a fragment and the number of the fragments covering a SNP (single nucleotide polymorphism) site are both very small compared with the length of a sequenced region and the total number of the fragments and introduces the parameterized haplotyping problems. With m fragments whose maximum length is k1, n SNP sites and the number of the fragments covering a SNP site no more than k2, our algorithms can solve the gapless MSR (Minimum SNP Removal) and MFR (Minimum Fragment Removal) problems in the time complexity O(nk1k2 + m log m + nk2 + mk1) and [Formula: see text] respectively. Since, the value of k1 and k2 are both small (about 10) in practice, our algorithms are more efficient and applicable compared with the algorithms of V. Bafna et al. of time complexity O(mn2) and O(m2n + m3), respectively.

scholarly journals Misannotation of multiple-nucleotide variants risks misdiagnosis

2019 ◽  
Vol 4 ◽  
pp. 145
Author(s):  
Matthew N. Wakeling ◽  
Thomas W. Laver ◽  
Kevin Colclough ◽  
Andrew Parish ◽  
Sian Ellard ◽  
...  
Keyword(s):  
Best Practices ◽  
False Negative ◽  
Simulated Data ◽  
Sequencing Analysis ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Public Resources ◽  
Next Generation Sequencing Analysis ◽  
Optimal Approach

Multiple Nucleotide Variants (MNVs) are miscalled by the most widely utilised next generation sequencing analysis (NGS) pipelines, presenting the potential for missing diagnoses that would previously have been made by standard Sanger (dideoxy) sequencing. These variants, which should be treated as a single insertion-deletion mutation event, are commonly called as separate single nucleotide variants. This can result in misannotation, incorrect amino acid predictions and potentially false positive and false negative diagnostic results. This risk will be increased as confirmatory Sanger sequencing of Single Nucleotide variants (SNVs) ceases to be standard practice. Using simulated data and re-analysis of sequencing data from a diagnostic targeted gene panel, we demonstrate that the widely adopted pipeline, GATK best practices, results in miscalling of MNVs and that alternative tools can call these variants correctly. The adoption of calling methods that annotate MNVs correctly would present a solution for individual laboratories, however GATK best practices are the basis for important public resources such as the gnomAD database. We suggest integrating a solution into these guidelines would be the optimal approach.

scholarly journals Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

2018 ◽  
Author(s):  
Dimitrios Kleftogiannis ◽  
Marco Punta ◽  
Anuradha Jayaram ◽  
Shahneen Sandhu ◽  
Stephen Q. Wong ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Low Frequency ◽  
Poisson Model ◽  
Real Data ◽  
Analytical Sensitivity ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Deep Sequencing Data ◽  
Targeted Deep Sequencing

AbstractBackgroundTargeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs).MethodsTo address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection.ResultsOur tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments.ConclusionsAmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve.

scholarly journals CRISPR/Cas9 inhibits rather than induces non-targeted DNA cleavage more likely to cause off-target single-nucleotide variants

2021 ◽  
Author(s):  
Ze Zhang ◽  
Yuanyuan Guo ◽  
Rongjia Zhang ◽  
Wuchen Yang ◽  
Zhengqing Xie ◽  
...  
Keyword(s):  
Dna Cleavage ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Free System ◽  
Cell Free System ◽  
Cell Extracts ◽  
Target Dna ◽  
Target Sequences

CRISPR/Cas9 gene targeting technology has become the most widely used gene editing technology in both plants and animals. However, substantial off-target effect remains as a major imperfection hindering its further application. Here, Nicotiana benthamiana leaf cell-free system was used to simulate in vivo environment. And the effects of different CRISPR/Cas9 components on DNA stability in cell-free system were studied to explore possible mechanisms causing CRISPR off-target. The results showed that overexpressing Cas9, nCas9 and dCas9 significantly inhibited DNA cleavage in the cell extracts. While overexpressing RNPs accelerated the target DNA cleavage but inhibited non-target DNA digestion in cell extracts, overexpressing nRNP and dRNP blocked the cleavage of either target or non-target sequences. Meanwhile, analysis of whole-genome sequencing data from mice and rice edited by different CRISPR tools revealed that the main off-target mutations were SNVs (single nucleotide variants), rather than Indels (insertions and deletions) that were readily induced by DNA double-strand breaks. The off-target sites did not match the conventionally predicted places but were PAM-rich sites preferred. Our study suggests that PAM-dependent binding without cleavage of CRISPR/Cas9 to non-target sequences may increase off-target mutation risks through impeding the necessary cleavage process for repairing spontaneous or environmentally induced non-targeted DNA mutations.

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